Could senescence phenotypes strike the balance to promote tumor dormancy?

A Conversation with ChatGPT on Contentious Issues in Senescence and Cancer Research

Artificial intelligence (AI) platforms, such as Generative Pretrained Transformer (ChatGPT), have achieved a high degree of popularity within the scientific community due to their utility in providing evidence-based reviews of the literature. However, the accuracy and reliability of the information output and the ability to provide critical analysis of the literature, especially with respect to highly controversial issues, has generally not been evaluated. In this work, we arranged a question/answer session with ChatGPT regarding several unresolved questions in the field of cancer research relating to therapy-induced senescence (TIS), including the topics of senescence reversibility, its connection to tumor dormancy, and the pharmacology of the newly emerging drug class of senolytics. ChatGPT generally provided responses consistent with the available literature, although occasionally overlooking essential components of the current understanding of the role of TIS in cancer biology and treatment. Although ChatGPT, and similar AI platforms, have utility in providing an accurate evidence-based review of the literature, their outputs should still be considered carefully, especially with respect to unresolved issues in tumor biology. SIGNIFICANCE STATEMENT: Artificial Intelligence platforms have provided great utility for researchers to investigate biomedical literature in a prompt manner. However, several issues arise when it comes to certain unresolved biological questions, especially in the cancer field. This work provided a discussion with ChatGPT regarding some of the yet-to-be-fully-elucidated conundrums of the role of therapy-induced senescence in cancer treatment and highlights the strengths and weaknesses in utilizing such platforms for analyzing the scientific literature on this topic.

The senescent mesothelial matrix accentuates colonization by ovarian cancer cells

Ovarian cancer is amongst the most morbid of gynecological malignancies due to its diagnosis at an advanced stage, a transcoelomic mode of metastasis, and rapid transition to chemotherapeutic resistance. Like all other malignancies, the progression of ovarian cancer may be interpreted as an emergent outcome of the conflict between metastasizing cancer cells and the natural defense mounted by microenvironmental barriers to such migration. Here, we asked whether senescence in coelom-lining mesothelia, brought about by drug exposure, affects their interaction with disseminated ovarian cancer cells. We observed that cancer cells adhered faster on senescent human and murine mesothelial monolayers than on non-senescent controls. Time-lapse epifluorescence microscopy showed that mesothelial cells were cleared by a host of cancer cells that surrounded the former, even under sub-confluent conditions. A multiscale computational model predicted that such colocalized mesothelial clearance under sub-confluence requires greater adhesion between cancer cells and senescent mesothelia. Consistent with the prediction, we observed that senescent mesothelia expressed an extracellular matrix with higher levels of fibronectin, laminins and hyaluronan than non-senescent controls. On senescent matrix, cancer cells adhered more efficiently, spread better, and moved faster and persistently, aiding the spread of cancer. Inhibition assays using RGD cyclopeptides suggested the adhesion was predominantly contributed by fibronectin and laminin. These findings led us to propose that the senescence-associated matrisomal phenotype of peritoneal barriers enhances the colonization of invading ovarian cancer cells contributing to the metastatic burden associated with the disease.